1. Use of AMSR-E Land Parameter Modeling and Retrievals for SMAP Algorithm Development Steven Chan Eni Njoku Joint AMSR Science Team Meeting Telluride, Colorado July 14-16, 2008

2. The SMAP Algorithm Development Testbed Purposes:  An L-band mission simulator (simulated TB’s to be as realistic as possible)  Modules capable of testing multiple algorithms subject to the same inputs Features:  Realistic orbital and instrument sampling  Global and continental scales  Annual cycle(s) Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008  An end-to-end Observing System Simulation Experiment (OSSE) for SMAP

3. The SMAP Algorithm Development Testbed Anticipated Benefits:  Investigate relative strengths/weaknesses of different retrieval algorithms  Impacts of pursuing different science/instrument/mission trades  Impacts of ancillary data uncertainties Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008  Realistic orbital and instrument sampling

4. Major Testbed Components Excerpted from SMAP Algorithm Development Testbed for MCR in Jun 2008  Land surface model (LSM) input  Forward microwave models (i.e. radiometer and radar) Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008  Environmental effects (e.g. Faraday rotation, galactic radiation)  Instrument effects (e.g. instrument precision, calibration errors)  Inverse models (e.g. radiometer, radar, and combined radar-radiometer)  Error analysis  Orbital and instrument sampling

5. Testbed Flowchart Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008 LSM Input Parameters Surface Temp Soil Texture Vegetation ‘Truth’ Soil Moisture Orbital/ Instrument Sampling Forward Models (radiometer/radar) Environmental Effects Instrument Effects TB,σ° Inverse Models (radiometer/radar) Retrieved Soil Moisture ● ● ●● ● ● Error Analysis

6. Orbital and Instrument Sampling Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008 Altitude = 670km Sampling Period = 42ms Antenna = 6m Incidence = 40° SMAP Ground Tracks

7. Orbital and Instrument Sampling (Radiometer) Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008 SMAP Instrument Sampling (boresight and antenna beam pattern)

8. Major Testbed Components Excerpted from SMAP Algorithm Development Testbed for MCR in Jun 2008  Land surface model (LSM) input  Forward microwave models (i.e. radiometer and radar) Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008  Environmental effects (e.g. Faraday rotation, galactic radiation)  Instrument effects (e.g. instrument precision, calibration errors)  Inverse models (e.g. radiometer, radar, and combined radar-radiometer)  Error analysis  Orbital and instrument sampling

9. Land Surface Model Input Parameters Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008 Current scheme: Use geophysical data fields from GLDAS Soil Moisture Surface Temperature Sand Fraction Vegetation Water Content Soil Temperature Clay Fraction

10. Advantages Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008  Antenna sampling not well addressed: cell size (above) >> SMAP footprint  Simulated TB’s may have QC issues due to unrealistic inputs  Inputs may introduce unreal spatial and temporal correlations  Convenience: one-stop portal of geophysical input data fields  Fields are consistent with the underlying land model that generates them Potential Limitations

11. Major Testbed Components Excerpted from SMAP Algorithm Development Testbed for MCR in Jun 2008  Land surface model (LSM) input  Forward microwave models (i.e. radiometer and radar) Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008  Environmental effects (e.g. Faraday rotation, galactic radiation)  Instrument effects (e.g. instrument precision, calibration errors)  Inverse models (e.g. radiometer, radar, and combined radar-radiometer)  Error analysis  Orbital and instrument sampling

12. First Step Towards More Realistic Inputs/Outputs Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008 Proposed scheme: Use AMSR-E data fields ( ) to first optimize forward model and then extend its frequency dependence to L-band frequency AMSR-E Soil Moisture Forward Model at 6.9 GHz Forward Model at 10.7 GHz Forward Model at 18.7 GHz Simulated TB’s at 6.9 GHz Simulated TB’s at 10.7 GHz Simulated TB’s at 18.7 GHz AMSR-E TB’s at 6.9 GHz AMSR-E TB’s at 10.7 GHz AMSR-E TB’s at 18.7 GHz Optimal Model Parameters at 6.9 GHz Optimal Model Parameters at 10.7 GHz Optimal Model Parameters at 18.7 GHz

13. First Step Towards More Realistic Inputs/Outputs Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008 Frequency (GHz) 20151050 6.9 10.718.7 1.4 Model Parameter (e.g. ω)  Use AMSR-E soil moisture and AMSR-E TB’s to determine optimal model parameters at a given frequency  Repeat the above procedure for other frequencies  Explore frequency dependence of optimal model parameters and extend (extrapolate) their values to L-band frequency Radiative Transfer Forward Model Ts: surface temperature, r’s: Fresnel reflectivities, τ: vegetation opacity ω: single-scattering albedo, h: surface roughness, Q: polarization mixing ratio

14. Simulated L-band TB (1 Day) Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008

15. Simulated L-band TB (2 Days) Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008

16. Simulated L-band TB (3 Days) Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008

17. Summary Steven K. Chan  Joint AMSR Science Team Meeting  Telluride, Colorado  Jul 14-16, 2008  SMAP Testbed as an end-to-end mission simulator  Simulated L-band observations to be as realistic as possible  AMSR-E data fields could be used to optimize forward model and extend its frequency dependence to L-band frequency, thus assisting the SMAP Testbed to generate realistic L-band observations